SEARCH · Engineering Papers

Results for “local dynamic operator”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Polynomial-time preparation of low-temperature Gibbs states for two-dimensional toric code

In this work, we propose a polynomial-time algorithm for preparing the Gibbs state of the two-dimensional toric code Hamiltonian at any temperature, starting from any initial state, significantly improving upon prior estimates that suggested exponential scaling with inverse temperature. We prove that fast mixing at low temperature for the two-dimensional toric code can be achieved by augmenting local jump operators with simple global jump operators, which enable efficient transitions between logical sectors. To establish tight lower bounds on the spectral gap, we introduce a new reduction method that eventually maps the problem to estimating the spectral gap of a perturbed graph Laplacian on a stair graph. Our proof also shows that the Lindblad dynamics with a digitally implemented low-temperature local Davies generator is able to efficiently drive the quantum state toward the ground state manifold.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Dispersion mechanisms of a tidal river junction in the Sacramento–San Joaquin Delta, California

In branching channel networks, such as in the Sacramento–San Joaquin River Delta, junction flow dynamics contribute to dispersion of ecologically important entities such as fish, pollutants, nutrients, salt, sediment, and phytoplankton. Flow transport through a junction largely arises from velocity phasing in the form of divergent flow between junction channels for a portion of the tidal cycle. Field observations in the Georgiana Slough junction, which is composed of the North and South Mokelumne rivers, Georgiana Slough, and the Mokelumne River, show that flow phasing differences between these rivers arise from operational, riverine, and tidal forcing. A combination of Acoustic Doppler Current Profile (ADCP) boat transecting and moored ADCPs over a spring–neap tidal cycle (May to June 2012) monitored the variability of spatial and temporal velocity, respectively. Two complementary drifter studies enabled assessment of local transport through the junction to identify small-scale intrajunction dynamics. We supplemented field results with numerical simulations using the SUNTANS model to demonstrate the importance of phasing offsets for junction transport and dispersion. Different phasing of inflows to the junction resulted in scalar patchiness that is characteristic of MacVean and Stacey’s (2011) advective tidal trapping. Furthermore, we observed small-scale junction flow features including a recirculation zone and shear layer, which play an important role in intra-junction mixing over time scales shorter than the tidal cycle (i.e., super-tidal time scales). Thus, the study period spanned open- and closed-gate operations at the Delta Cross Channel. Synthesis of field observations and modeling efforts suggest that management operations related to the Delta Cross Channel can strongly affect transport in the Delta by modifying the relative contributions of tidal and riverine flows, thereby changing the junction flow phasing.

42 ENGINEERING↗

DOE OSTI2022

Local correlation-based transition models for high-Reynolds-number wind-turbine airfoils

Abstract. Modern wind-turbine airfoil design requires robust performance predictions for varying thicknesses, shapes, and appropriate Reynolds numbers. The airfoils of current large offshore wind turbines operate with chord-based Reynolds numbers in the range of 3–15 million. Turbulence transition in the airfoil boundary layer is known to play an important role in the aerodynamics of these airfoils near the design operating point. While the lack of prediction of lift stall through Reynolds-averaged Navier–Stokes (RANS) computational fluid dynamics (CFD) is well known, airfoil design using CFD requires the accurate prediction of the glide ratio (L/D) in the linear portion of the lift polar. The prediction of the drag bucket and the glide ratio is greatly affected by the choice of the transition model in RANS CFD of airfoils. We present the performance of two existing local correlation-based transition models – one-equation model (γ− SA) and two-equation model (γ-Reθt‾- SA) coupled with the Spalart–Allmaras (SA) RANS turbulence model – for offshore wind-turbine airfoils operating at a high Reynolds number. We compare the predictions of the two transition models with available experimental and CFD data in the literature in the Reynolds number range of 3–15 million including the AVATAR project measurements of the DU00-W-212 airfoil. Both transition models predict a larger L/D compared to fully turbulent results at all Reynolds numbers. The two models exhibit similar behavior at Reynolds numbers around 3 million. However, at higher Reynolds numbers, the one-equation model fails to predict the natural transition behavior due to early transition onset. The two-equation transition model predicts the aerodynamic coefficients for airfoils of various thickness at higher Reynolds numbers up to 15 million more accurately compared to the one-equation model. As a result, the two-equation model predictions are more comparable to the predictions from eN transition model. However, a limitation of this model is observed at very high Reynolds numbers of around 12–15 million where the predictions are very sensitive to the inflow turbulent intensity. The combination of the two-equation transition model coupled with the Spalart–Allmaras (SA) RANS turbulence model is a good method for performance prediction of modern wind-turbine airfoils using CFD.

17 WIND ENERGY↗

DOE OSTI2021

Carbon and Hydrocarbon Particle Seeding in Air-Breathing Rotating Detonation Engine

Within the power generation community, the rotating detonation engine (RDE) is only growing in popularity with its increased performance, simple mechanism, and operation. Although significant testing is underway to characterize the RDE for integration with conventional gas turbines, this entire system is still at a relatively low technology readiness level. In the midst of RDE research, there is an initiative to understand solid particle seeding effects in the detonation performance. Under investigation at the University of Central Florida is a Department of Energy (DOE) 15.24 cm (6 in.) RDE, with a solid particle seeder in parallel with its H2 and air flow lines. Previous work on this system involved carbon particle detonation; however, the tested particles were taken one step further to include more sustainable, greener hydrocarbon particles. Testing of powdered sugar, peanut flour, and cornstarch, along with previous carbon black tests have shown not only successful detonability, but a noticeable effect on the detonation wave dynamics. Side-by-side with a particle burning model being developed, an operational map can be determined for the hydrocarbon particles particularly, which can be tuned with the local flow conditions to achieve peak operability while replacing fuels with sustainable alternatives that could even be grown.

Engineering↗

NASA NTRS1996

Fuzzy Q-Learning for Generalization of Reinforcement Learning

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

Berenji, Hamid R.↗

NASA NTRS2017

3D Realistic Modeling of the Interaction of Quiet-Sun Magnetic Fields with the Chromosphere

High-resolution observations and 3D simulations suggest that a local dynamo operates near the surface and produces ubiquitous small-scale magnetic elements, thus contributing to the magnetic carpet in the photosphere and to the magnetic structure and dynamics of the solar atmosphere. It appears that the traditional mechanisms of chromospheric energy and mass transport by acoustic waves and shocks are likely to play a secondary role; instead, the primary drivers in the energetics and dynamics of the chromosphere and transition region are small-scale, previously unresolved, quiet-Sun magnetic fields. These fields appear as ubiquitous, rapidly changing (on the scale of a few seconds), tiny magnetic loops and magnetized vortex tubes. Questions then arise about their origin and dynamics in the chromosphere, their links to magnetic fields in the photosphere, and their role in the energy storage and exchange between subsurface layers and the chromosphere. In the talk we will present results of 3D radiative MHD simulations obtained with the StellarBox code and discuss the energetics and dynamical interlinks between the subphotospheric layers and low chromosphere, their effects on the structure of the chromosphere, and signatures of the fine-scale magnetic features in high-resolution spectro-polarimetric observations.

Quie-Sun↗

NASA NTRSDate not supplied

Development Efforts and Status of Plume-Surface Interaction Capabilities for Propulsive Landing Systems

Rocket plume-surface interaction is a multi-phase problem characterized by plume flow physics, erosion physics, and ejecta dynamics. All propulsive landers will experience plume-surface interaction. The risks posed by such effects can vary greatly as a function of the local environment, lander concept of operations, configuration, and physical scale. Prior Lunar and Martian landers have overcome challenges posed by these environments, on the basis of scaled ground testing and subsequent flight experience, but the landing systems for present and future missions are planning to operate increasingly outside of NASA's current experience with plume-surface interaction. This presentation discusses the current efforts and status of activities within NASA to progress understanding of fundamental plume-surface interaction physics, the capability to predict resulting environments and effects, and the definition of implications for current and future Lunar and planetary landing systems.

Landing↗

DOE OSTI2023

Impact of Soret effect on hydrogen and helium retention in PFC tungsten under ELM-like conditions

Abstract In our previous work, we have demonstrated using nonequilibrium molecular-dynamics simulations that the fluxes of helium and self-interstitial atoms in the presence of a thermal gradient in tungsten are directed opposite to the heat flux, indicating that species transport is governed by a Soret effect, namely, thermal-gradient-driven diffusion, characterized by a negative heat of transport that drives species transport uphill, i.e. from the cooler to the hot regions of the tungsten sample. In this work, the findings of our thermal and species transport analysis have been implemented in our cluster-dynamics code, Xolotl, which has been used to compute temperature and species profiles over spatiotemporal scales representative of plasma-facing component (PFC) tungsten under typical reactor operating conditions, including extreme heat loads at the plasma-facing surface characteristic of plasma instabilities that induce edge localized modes (ELMs). We demonstrate that the steady-state species profiles, when properly accounting for the Soret effect, vary significantly from those where temperature-gradient-driven transport is not accounted for and discuss the implications of such a Soret effect on the response to plasma exposure of plasma-facing tungsten. Although our cluster-dynamics simulations do not yet include self-clustering of helium or hydrogen blister formation, our simulation results show that the Soret effect substantially reduces helium and hydrogenic species retention inside PFC tungsten.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Outer Radiation Belt Dynamics During the October 2012 Storm Revisited: Rapid Inward Radial Transport From a Dynamic Outer Boundary

Earth's outer radiation belt electron flux is highly variable and can be enhanced by over an order of magnitude over timescales less than one day, as observed during the October 2012 storm. Previous studies of this storm (e.g., Reeves et al., 2013, https://doi.org/10.1126/science.1237743) have invoked local acceleration to explain this. However, here, we argue that the observations can instead be explained by fast inward radial transport. One method often invoked to distinguish between these two acceleration processes is the existence of local peaks in electron phase space density (PSD) as a function of L* at fixed first, M, and second, K, adiabatic invariants. However, this method relies on the assumption that the evolution of the PSD as a function of L* occurs over timescales slower than the satellite orbital period. Here, high spatiotemporal resolution data from the Global Positioning System (GPS) spacecraft constellation is used to show that enhancements in the PSD occur during the October 2012 storm over short timescales not resolvable by the Van Allen Probes. In addition, Geostationary Operational Environmental Satellite spacecraft data also indicate that these enhancements are consistent with relativistic electron injections. A radial diffusion model is shown to reproduce the PSD dynamics observed by the Van Allen Probes, once rapid variations at the simulation outer boundary are included, consistent with GPS data. This verifies that apparently “locally growing” peaks in PSD along high apogee satellite orbits can be produced by fast inward radial transport without requiring the action of any local acceleration processes.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

mosartwmpy: A Python implementation of the MOSART-WM coupled hydrologic routing and water management model

mosartwmpy is a Python implementation of the Model for Scale Adaptive River Transport with Water Management (MOSART-WM). This new version retains the functionality of the legacy model (written in FORTRAN) while providing new features to enhance user experience and extensibility. MOSART is a large-scale river-routing model used to study riverine dynamics of water, energy, and biogeochemistry cycles across local, regional, and global scales (Li et al., 2013). The WM component introduced by Voisin et al. (2013) represents river regulation through reservoir storage and release operations, diversions from reservoir releases, and allocation to sectoral water demands. Each reservoir release is independently calibrated using long-term mean monthly inflow into the reservoir, long-term mean monthly demand associated with this reservoir, and reservoir goals (flood control, irrigation, recreation, etc.). Generic monthly pre-release rules and storage targets are set up for individual reservoirs; however, those releases are updated annually for inter-annual variability (dry or wet year) and daily for environmental constraints such as flow minimum release and minimum/maximum storage levels. The WM model allows an evaluation of the impact of water management over multiple river basins at once (global, continental scales) and with consistent representation of human operations over the full domain.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human agency is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems towards either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services towards some human end. We trace the salient features of modeled representations of human systems by organizing the typology around three key questions: 1) Who are the modeled actors in MSD systems? 2) What are their modeled actions? 3) How and for what purpose are these actors and actions operationalized in a computational model? The typology is used to critically examine existing models and chart the frontier of future human systems modeling for MSD research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Capturing Pressure Oscillations in Numerical Simulations of Internal Combustion Engines

In an earlier publication, the authors compared numerical predictions of the mean cylinder pressure of diesel and dual-fuel combustion, to that of measured pressure data from a medium-speed, large-bore engine. In these earlier comparisons, measured data from a flush-mounted in-cylinder pressure transducer showed notable and repeatable pressure oscillations which were not evident in the mean cylinder pressure predictions from computational fluid dynamics (CFD). In this paper, the authors present a methodology for predicting and reporting the local cylinder pressure consistent with that of a measurement location. Such predictions for large-bore, medium-speed engine operation demonstrate pressure oscillations in accordance with those measured. The temporal occurrences of notable pressure oscillations were during the start of combustion and around the time of maximum cylinder pressure. With appropriate resolutions in time steps and mesh sizes, the local cell static pressure predicted for the transducer location showed oscillations in both diesel and dual-fuel combustion modes which agreed with those observed in the experimental data. Fast Fourier transform (FFT) analysis on both experimental and calculated pressure traces revealed that the CFD predictions successfully captured both the amplitude and frequency range of the oscillations. Furthermore, resolving propagating pressure waves with the smaller time steps and grid sizes necessary to achieve these results required a significant increase in computer resources.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

Quantum Regge trajectories and the Virasoro analytic bootstrap

Every conformal field theory (CFT) above two dimensions contains an infinite set of Regge trajectories of local operators which, at large spin, asymptote to “double-twist” composites with vanishing anomalous dimension. In two dimensions, due to the existence of local conformal symmetry, this and other central results of the conformal bootstrap do not apply. We incorporate exact stress tensor dynamics into the CFT 2 analytic bootstrap, and extract several implications for AdS 3 quantum gravity. Our main tool is the Virasoro fusion kernel, which we newly analyze and interpret in the bootstrap context. The contribution to double-twist data from the Virasoro vacuum module defines a “Virasoro Mean Field Theory” (VMFT); its spectrum includes a finite number of discrete Regge trajectories, whose dimensions obey a simple formula exact in the central charge c and external operator dimensions. We then show that VMFT provides a baseline for large spin universality in two dimensions: in every unitary compact CFT 2 with c > 1 and a twist gap above the vacuum, the double-twist data approaches that of VMFT at large spin ℓ. Corrections to the large spin spectrum from individual non-vacuum primaries are exponentially small in √ℓ for fixed c. We analyze our results in various large c limits. Further applications include a derivation of the late-time behavior of Virasoro blocks at generic c; a refined understanding and new derivation of heavy-light blocks; and the determination of the cross-channel limit of generic Virasoro blocks. We deduce non-perturbative results about the bound state spectrum and dynamics of quantum gravity in AdS 3 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1990

Simultaneous conjugate observations of dynamic variations in high-latitude dayside convection due to changes in IMF By

Data from two conjugate HF radars currently operating at Goose Bay (Labrador) and the Halley Station (Antarctica), obtained for a single 45-min period about local noon on April 22, 1988, were used to study the near-instantaneous conjugate two-dimensional patterns of plasma convection in the vicinity of the cusp. In particular, the response of these plasma convection patterns to changes in the By component of the IMF was examined. Results indicate that, under quasi-stationary IMF conditions, the conjugate convection patterns are quite similar to the synthesized patterns of Heppner and Maynard (1987) and that the patterns respond rapidly to changes in the IMF By component. Results also show that transitions between convection states begin to occur within minutes of the time that an IMF state change is incident on the magnetospheric boundary, and that the convection reconfigurations expand poleward, completely filling the field of view of an HF radar within 6 min of the time of onset.

Greenwald, R. A.↗

DOE OSTI2021

Blockchain-Enabled Cyber-Secure Microgrid Control Using Consensus Algorithm

This paper proposes a distributed control method based on a consensus algorithm for distributed energy resources (DERs) using blockchain as a secure communication medium for cyber resilience. Each DER communicates with a local blockchain server that is maintained by the distributed ledger technology to allow for securely sharing local measurements among neighbouring assets to achieve the global control objectives, i.e., voltage and frequency regulation as well as accurate power sharing among the DERs, including collective grid-forming capability. To prove that the distributed control can retain system stability under a blockchain-induced variable communication delay, Lyapunov function-based stability analysis is carried out. This paper demonstrates the concept on an 11-bus test case developed in MATLAB Simulink, which has been modified from the IEEE 9-bus test case, to study dynamic operations of the five inverter-based DERs working with a blockchain-induced variable delay. The results validate the superior performance of the proposed control method, compared to heavily compromised operations of the other test cases without the security measure, affected by heavy communication delays and communication interruptions.

blockchains↗

DOE OSTI2022

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

SU-C-BRD-03: Closing the Loop On Virtual IMRT QA

Purpose: To develop an algorithm that predicts a priori IMRT QA passing rates. Methods: 416 IMRT plans from all treatment sites were planned in Eclipse version 11 and delivered using a dynamic sliding window technique on Clinac iX or TrueBeam linacs (Varian Medical Systems, Palo Alto, CA). The 3%/3mm and 2%/2mm local distance to agreement (DTA) were recorded during clinical operations using a commercial 2D diode array (MapCHECK 2, Sun Nuclear, Melbourne, FL). Each plan was characterized by 37 metrics that describe different failure modes between the calculated and measured dose. Machine-learning algorithms (MLAs) were trained to learn the relation between the plan characteristics and each passing rate. Minimization of the cross validated error, together with maximum a posteriori estimation (MAP), were used to choose the model parameters. Results: 3%/3mm local DTA can be predicted with an error smaller than 3% for 98% of the plans. For the remaining 2% of plans, the residual error was within 5%. For 2%/2mm local DTA passing rates, 96% percent of the plans were successfully predicted with an error smaller than 5%. All high-risk plans that failed the 2%/2mm local criteria were correctly identified by the algorithm. The most important metric to describe the passing rates was determined to be the MU per Gray (modulation factor). Conclusions: Logs files and independent dose calculations have been suggested as possible substitutes for measurement based IMRT QA. However, none of these methods answer the fundamental question of whether a plan can be delivered with a clinically acceptable error given the limitations of the linacs and the treatment planning system. Predicting the IMRT QA passing rates a priori closes that loop. For additional robustness, virtual IMRT QA can be combined with Linac QA and log file analysis to confirm appropriate delivery.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

ANALYSIS OF CORONAL RAIN OBSERVED BY IRIS , HINODE /SOT, AND SDO /AIA: TRANSVERSE OSCILLATIONS, KINEMATICS, AND THERMAL EVOLUTION

Coronal rain composed of cool plasma condensations falling from coronal heights along magnetic field lines is a phenomenon occurring mainly in active region coronal loops. Recent high-resolution observations have shown that coronal rain is much more common than previously thought, suggesting its important role in the chromosphere-corona mass cycle. We present the analysis of MHD oscillations and kinematics of the coronal rain observed in chromospheric and transition region lines by the Interface Region Imaging Spectrograph (IRIS) , the Hinode Solar Optical Telescope (SOT), and the Solar Dynamics Observatory ( SDO) Atmospheric Imaging Assembly (AIA). Two different regimes of transverse oscillations traced by the rain are detected: small-scale persistent oscillations driven by a continuously operating process and localized large-scale oscillations excited by a transient mechanism. The plasma condensations are found to move with speeds ranging from few km s{sup −1} up to 180 km s{sup −1} and with accelerations largely below the free-fall rate, likely explained by pressure effects and the ponderomotive force resulting from the loop oscillations. The observed evolution of the emission in individual SDO /AIA bandpasses is found to exhibit clear signatures of a gradual cooling of the plasma at the loop top. We determine the temperature evolution of the coronal loop plasma using regularized inversion to recover the differential emission measure (DEM) and by forward modeling the emission intensities in the SDO /AIA bandpasses using a two-component synthetic DEM model. The inferred evolution of the temperature and density of the plasma near the apex is consistent with the limit cycle model and suggests the loop is going through a sequence of periodically repeating heating-condensation cycles.

79 ASTRONOMY AND ASTROPHYSICS↗